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Part 7 of a beginner-friendly series on learning Python from scratch. In Part 6, we learned to write reusable functions. Now it's time to make those functions work in the real world: reading data from files, handling things when they go wrong, and using code other people have written. This is where
World of Claudecraft is a free, browser-based MMORPG. No download, no signup wall, you open a tab and you are in. It is open source, and most of it has been built by working alongside Claude rather than writing every line by hand. Check it out at: https://worldofclaudecraft.com/ I started it partly
enabling productivity: exploring GitHub Copilot JetBrains new features and Claude agent integration Every quarter, an IDE upgrades and claims to change your workflow. Most don’t. This one does. With the June 2026 release, GitHub Copilot ships a dense slate of upgrades for JetBrains IDEs—wrapping cor
The brief was approved. Scope defined, questions closed, acceptance criteria written. The obvious move was to start building. I ran the Plan phase first. Planning and the Plan phase are not the same thing. Every engineer plans. Sprint boards. Jira tickets. A rough sequence before a large refactor st
Every atomic-CSS system eventually hits the same wall: the built-in breakpoints and pseudo-classes are great — until the day you need something they never shipped with. A brand-specific selector. A retina-display query. A tablet breakpoint that doesn't match any of the defaults. Most tools force you
Sandi Metz wrote The Wrong Abstraction in 2016. It keeps resurfacing — in high-scoring HN threads, architecture Slack channels, and code review comments — whenever a team is staring at a function that started as a clean DRY consolidation and has since acquired seven parameters, three feature flags,
Cross-posted from my blog. Canonical version: https://launchsoloai.com/insights/runcap-vs-langfuse-vs-litellm-ai-cost-control You let a coding agent loose on a task. It loops. It re-reads the same files, re-summarizes the same context, retries the same failing call. Forty minutes later you check the
Between 2015 and 2021, India produced over 100 unicorns. Capital was abundant, and the prevailing logic of growing the user base and worrying about monetisation later reflected a genuine belief that scale would eventually take care of the economics.
Whether the Autopilot system was truly active, overridden, or malfunctioning likely won't be resolved until investigators finish combing through the vehicle's data logs.
We would often like to get a qualitative sense of a target model’s behaviors in important distributions (e.g. deployment, RL training, or evals). For example, we might want to discover novel behaviors, figure out what causes some target behavior to occur, or find surprising correlations between beha
The loop takes agentic AI a step further, by authorizing a swarm of agents to work continuously in the background, endlessly.
The AI developer tools consolidation continues apace, with news that Cursor has snapped up open-source coding assistant Continue — its The post Cursor quietly acquires Continue, an open-source alternative to GitHub Copilot appeared first on The New Stack.
Multiple WordPress plugins from ShapedPlugin were compromised in a supply chain attack after unknown threat actors managed to tamper with the official release channels and push backdoor code. "Attackers compromised the vendor's build and distribution pipeline, injecting backdoor code into Pro plugin
I just started your Generative AI for Everyone course, and I already feel this is the beginning of a new chapter in my life. Thank you for making this topic so clear and inspiring for learners like me. 1 post - 1 participant Read full topic
I have been experimenting with multi-agent systems and recently started building a DeepResearch-style agent workflow to understand what goes into a real Agentic AI application. The first version is intentionally simple, but the goal is not just another “LLM + tool call” demo. I’m trying to learn the
OpenAI introduces new Daybreak tools, including Codex Security and GPT-5.5-Cyber, to help organizations find, validate, and patch vulnerabilities at scale.
OpenAI introduces Patch the Planet, a Daybreak initiative helping open-source maintainers find, validate, and fix vulnerabilities with AI and expert review.
Why one-hot encoding isn’t always the best approach, and alternative encodings The post Encoding Categorical Data for Outlier Detection appeared first on Towards Data Science.
SQL is the industry standard for high-performance structured data analysis. However, expressing complex procedural logic, scientific computations, advanced string manipulations, or machine learning workflows in pure SQL can be highly challenging, if not impossible. That kind of work is better done w
Cybersecurity researchers have disclosed details of four vulnerabilities in Dify, an open-source agentic workflow platform with more than 146,000 GitHub stars, that could allow attackers to stealthily read artificial intelligence (AI) conversions from other customers' applications without requiring
